Measuring the accuracy of electronic health record-based phenotyping in the <i>All of Us</i> Research Program to optimize statistical power for genetic association testing
EHR-based phenotyping presents a bottleneck for maximizing power to detect novel risk alleles in All of Us, as well as a potential source of differential outcome misclassification that researchers should be aware of. We discuss the implications of this as well as potential mitigation strategies.
Authors
- Yi-Wen Hsiao (ORCID: https://orcid.org/0000-0002-9261-0353)
- Pei-Chen Peng (ORCID: https://orcid.org/0000-0002-5004-4322)
- John Baierl
- Paul D. P. Pharoah
- Michelle R Jones
Institutions
- Cedars-Sinai Medical Center (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2026-01-03
- DOI
- https://doi.org/10.1093/jamia/ocaf234
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00